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Who Endorses Amnesty? An Original Survey from Morocco's Casablanca Region Assessing Citizen Support for Regularizing Clandestine Migrants

Published online by Cambridge University Press:  15 January 2019

Matt Buehler
Affiliation:
University of Tennessee
Kyung Joon Han
Affiliation:
University of Tennessee
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Abstract

To deal with the growing migrant crisis in North Africa, several states have considered granting amnesty to foreign displaced persons (both economic migrants and potential refugees) who have entered their territories clandestinely. Morocco has taken the lead in this policy approach, launching two successful amnesty campaigns in 2014 and 2017 that regularized the status of approximately 40,000 displaced persons in total. While policymakers in many North African states increasingly see this policy as a viable solution, it is less understood how ordinary citizens view such regularization policies. Hence, this article inquires: under what conditions do ordinary native citizens support regularizing clandestine migrants and refugees? Further, what factors correlate with either higher or lower levels of public support for (or opposition to) regularization campaigns? Drawing on an original representative public opinion poll from Morocco's Casablanca-Settat region completed in 2017, this article finds that more than 59 percent of native citizens of Morocco support these regularization campaigns. Particularly, Moroccans who were wealthier, female, and ethnic minorities (black Moroccans) endorsed regularization more strongly. By contrast, Moroccans opposed regularization when they had concerns about whether displaced persons hurt the economy, undermine cultural traditions, and reduce stability.

Information

Type
Special Focus: Reflections on the Geopolitics of Refugees and Displaced Persons
Copyright
Copyright © Middle East Studies Association of North America, Inc. 2019 
Figure 0

Figure 1: Correlates of support for the regularization program.

Note: Positive coefficients denote higher support for migrant regularization; negative ones denote opposition. Standard errors in parentheses. *** p 
Figure 1

Figure 2: Predicted probabilities of the attitudes toward the regularization program.

Note: Circles indicate predicted probabilities and lines at their 95 percent confidence interval. The probabilities are calculated with the result of Figure 1’s model. “Agree with regularization” indicates the response of “Agree” to the question on regularization program (=4). “Disagree with regularization” indicates the response of “Disagree” to the question (=2). All the other variables are fixed at their mean level when predicted probabilities are calculated. Thorough predicted probabilities for all the categories of the dependent variable are presented in the Appendix.
Supplementary material: File

Buehler and Han supplementary material

Appendix

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